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Channel 9 is a community. We bring forward the people behind our products and connect them with those who use them. We think there is a great future in software and we're excited about it. We want the community to participate in the ongoing conversation. This is the heart of Channel 9. We talk about our work but listen to the customer.https://channel9.msdn.com/Tags/natural+language+processing
enThu, 14 Dec 2017 02:27:54 GMTThu, 14 Dec 2017 02:27:54 GMTRev99125Cognitive Services Episode 6 - Document routing & tagging with the Text Analytics & the Entity Linking APIsSo far in this course, we saw the high level AI concepts and we built a chatbot bound to a LUIS app. We also saw how to take advantage of the Linguistic Analysis API to perform natural search queries against external data sources. In this episode, we will send documents to our chatbot that will automatically tag and route them into a document management system thanks to Text Analytics, Entity Linking & Language Understanding Intelligent Service. ]]>https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-6-Document-routing--tagging-with-the-Text-Analytics--the-Entity-Linking-ASo far in this course, we saw the high level AI concepts and we built a chatbot bound to a LUIS app. We also saw how to take advantage of the Linguistic Analysis API to perform natural search queries against external data sources. In this episode, we will send documents to our chatbot that will automatically tag and route them into a document management system thanks to Text Analytics, Entity Linking &amp; Language Understanding Intelligent Service. 888https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-6-Document-routing--tagging-with-the-Text-Analytics--the-Entity-Linking-A
Fri, 22 Sep 2017 19:29:34 GMThttps://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-6-Document-routing--tagging-with-the-Text-Analytics--the-Entity-Linking-AStephane EyskensStephane Eyskens0https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-6-Document-routing--tagging-with-the-Text-Analytics--the-Entity-Linking-A/RSSNatural Language Processingbot frameworkbot frameworkCognitive Services Episode 5 - Natural search with the Linguistics APISo far in this course, we saw the high level AI concepts and we built a chatbot bound to a LUIS app. Our bot is already able to respond to IT-related questions and can tackle day-to-day conversations thanks to QnA Maker.

While QnA Maker is a great tool for textual questions/answers scenarios, it cannot be used when dealing with documents or data stored within a database and customers are not always willing to relocate their information into QnA Maker even when feasible.

In this episode, we'll see how to take advantage of another Cognitive Service, namely the Linguistic Analysis API to perform Natural Search Queries against external sources of information. I will show two use-cases: querying a SharePoint document center and interacting with a SQL database but the principles depicted here may be used to query any kind of information system.

]]>https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-5-Natural-search-with-the-Linguistics-APISo far in this course, we saw the high level AI concepts and we built a chatbot bound to a LUIS app. Our bot is already able to respond to IT-related questions and can tackle day-to-day conversations thanks to QnA Maker. While QnA Maker is a great tool for textual questions/answers scenarios, it cannot be used when dealing with documents or data stored within a database and customers are not always willing to relocate their information into QnA Maker even when feasible. In this episode, we'll see how to take advantage of another Cognitive Service, namely the Linguistic Analysis API to perform Natural Search Queries against external sources of information. I will show two use-cases: querying a SharePoint document center and interacting with a SQL database but the principles depicted here may be used to query any kind of information system. 925https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-5-Natural-search-with-the-Linguistics-API
Fri, 08 Sep 2017 12:49:06 GMThttps://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-5-Natural-search-with-the-Linguistics-APIStephane EyskensStephane Eyskens3https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-5-Natural-search-with-the-Linguistics-API/RSSNatural Language ProcessingAIbot frameworkCognitive Services Episode 3 - Deep dive into LUIS and ChatbotsEpisode 1 was about analyzing what's available in the Microsoft ecosystem in terms of artificial intelligence. In Episode 2, we setup the foundations to get us started with a minimal bot & we saw the typical steps involved in creating & consuming a Cognitive Service.In this demo-intensive episode, we'll first see what the challenges are when dealing with natural language and building chatbots. We'll then capitalize on what we've done already, by adding a LUIS layer to our bot. I will not only explain how LUIS works but I'll also give you concrete hands-on demos out of real world experience. ]]>https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-3-Deep-dive-into-LUIS-and-ChatbotsEpisode 1 was about analyzing what's available in the Microsoft ecosystem in terms of artificial intelligence. In Episode 2, we setup the foundations to get us started with a minimal bot &amp; we saw the typical steps involved in creating &amp; consuming a Cognitive Service.In this demo-intensive episode, we'll first see what the challenges are when dealing with natural language and building chatbots. We'll then capitalize on what we've done already, by adding a LUIS layer to our bot. I will not only explain how LUIS works but I'll also give you concrete hands-on demos out of real world experience. 1604https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-3-Deep-dive-into-LUIS-and-Chatbots
Sat, 26 Aug 2017 08:47:26 GMThttps://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-3-Deep-dive-into-LUIS-and-ChatbotsStephane EyskensStephane Eyskens4https://channel9.msdn.com/Blogs/MVP-Azure/Cognitive-Services-Episode-3-Deep-dive-into-LUIS-and-Chatbots/RSSNatural Language ProcessingAIbot frameworkAI 智能服務應用大賽 - 3+5 多重獎勵2017 AI 智能服務應用大賽 - 北市府資訊局特別加碼！

]]>https://channel9.msdn.com/Blogs/Channel9Taiwan/AIContest2017-bonus2017 AI 智能服務應用大賽 - 北市府資訊局特別加碼！ 針對 AI &#43; ChatBot 主題，將不限開發何種通訊平台 ChatBot，參賽資&#26684;如下： 使用 Microsoft Bot Framework使用至少一種 Microsoft Cognitive Service APIs (Ex: LUIS 語意理解等)本組題目可選擇：自訂題目 (不限題目均可參賽)北市府市政 ChatBot 應用競賽組 (需使用北市府市政網站常見問答開發 ChatBot，報名此組將有機會獲得額外的 NTD$5,000 獎金並參與北市府舉辦的第二階段選拔，爭取後續合作機會)32https://channel9.msdn.com/Blogs/Channel9Taiwan/AIContest2017-bonus
Tue, 18 Apr 2017 16:12:06 GMThttps://channel9.msdn.com/Blogs/Channel9Taiwan/AIContest2017-bonusJennifer Chiu, JadeChangJennifer Chiu, JadeChang0https://channel9.msdn.com/Blogs/Channel9Taiwan/AIContest2017-bonus/RSSNatural Language ProcessingAIchatbot frameworkbot frameworkBots 101 - Scenarios for botsLet us take a look at real world scenarios for bots and how they can be used for solving real user needs. ]]>https://channel9.msdn.com/Series/Explain/Bots-101-Scenarios-for-botsLet us take a look at real world scenarios for bots and how they can be used for solving real user needs. 980https://channel9.msdn.com/Series/Explain/Bots-101-Scenarios-for-bots
Tue, 28 Feb 2017 17:29:11 GMThttps://channel9.msdn.com/Series/Explain/Bots-101-Scenarios-for-botsMat VellosoMat Velloso2https://channel9.msdn.com/Series/Explain/Bots-101-Scenarios-for-bots/RSSNatural Language ProcessingSkypeSpeech RecognitionCortanabot frameworkbot frameworkA Practical Guide to Neural Machine TranslationIn the last two years, attentional-sequence-to-sequence neural models have become the state-of-the-art in machine translation, far surpassing the accuracy phrasal translation systems of in many scenarios. However, these Neural Machine Translation (NMT) systems are not without their difficulties: training a model on a large-scale data set can often take weeks, and they are typically much slower at decode time than a well-optimized phrasal system. In addition, robust training of these models often relies on particular 'recipes' that are not well-explained or justified in the literature. In the talk, I will describe a number of tricks and techniques to substantially speed up training and decoding of large-scale NMT systems. These techniques - which vary between algorithmic and engineering-focused - reduced the time required to train a large-scale NMT from two weeks to two days, and improved the decoding speed to match that of a well-optimized phrasal MT system. In addition, I will attempt to give empirical and intuitive justification for many of the choices made regarding architecture, optimization, and hyperparameters. Although this talk will primarily focus on NMT, the techniques described here should generalize to a number of other models based on sequence-to-sequence and recurrent neural networks, such as caption generation and conversation agents.

See more on this video at https://www.microsoft.com/en-us/research/video/practical-guide-neural-machine-translation/

]]>https://channel9.msdn.com/Shows/Microsoft-Research/A-Practical-Guide-to-Neural-Machine-TranslationIn the last two years, attentional-sequence-to-sequence neural models have become the state-of-the-art in machine translation, far surpassing the accuracy phrasal translation systems of in many scenarios. However, these Neural Machine Translation (NMT) systems are not without their difficulties: training a model on a large-scale data set can often take weeks, and they are typically much slower at decode time than a well-optimized phrasal system. In addition, robust training of these models often relies on particular 'recipes' that are not well-explained or justified in the literature. In the talk, I will describe a number of tricks and techniques to substantially speed up training and decoding of large-scale NMT systems. These techniques - which vary between algorithmic and engineering-focused - reduced the time required to train a large-scale NMT from two weeks to two days, and improved the decoding speed to match that of a well-optimized phrasal MT system. In addition, I will attempt to give empirical and intuitive justification for many of the choices made regarding architecture, optimization, and hyperparameters. Although this talk will primarily focus on NMT, the techniques described here should generalize to a number of other models based on sequence-to-sequence and recurrent neural networks, such as caption generation and conversation agents. See more on this video at https://www.microsoft.com/en-us/research/video/practical-guide-neural-machine-translation/ 4967https://channel9.msdn.com/Shows/Microsoft-Research/A-Practical-Guide-to-Neural-Machine-Translation
Wed, 04 Jan 2017 21:17:59 GMThttps://channel9.msdn.com/Shows/Microsoft-Research/A-Practical-Guide-to-Neural-Machine-TranslationTukCardenTukCarden1https://channel9.msdn.com/Shows/Microsoft-Research/A-Practical-Guide-to-Neural-Machine-Translation/RSSMicrosoft ResearchMSRNatural Language ProcessingAIArtificial IntelligenceMeet the presenter bot, a bot that presents about botsPresenterBot is an open source project to demonstrate some of the technologies behind Microsoft Bot Framework, LUIS, Skype and Bing Speech.

]]>https://channel9.msdn.com/Series/Explain/Meet-the-presenter-bot-a-bot-that-presents-about-botsPresenterBot is an open source project to demonstrate some of the technologies behind Microsoft Bot Framework, LUIS, Skype and Bing Speech. You can find the source code here: https://github.com/matvelloso/presenterbot 294https://channel9.msdn.com/Series/Explain/Meet-the-presenter-bot-a-bot-that-presents-about-bots
Thu, 27 Oct 2016 18:48:06 GMThttps://channel9.msdn.com/Series/Explain/Meet-the-presenter-bot-a-bot-that-presents-about-botsMat VellosoMat Velloso5https://channel9.msdn.com/Series/Explain/Meet-the-presenter-bot-a-bot-that-presents-about-bots/RSSNatural Language ProcessingSpeech APIbot frameworkbot framework//Build Reaction - Cortana and the Bot FrameworkBots (or conversation agents) are rapidly becoming an integral part of your users' digital experience – they are as vital a way for users to interact with a service or application as is a web site or a mobile experience. Bots can also integrate with digital assistants like Cortana. Developers writing bots all face the same problems: bots require basic I/O; they must have language and dialog skills; and they must connect to users – preferably in any conversation experience and language the user chooses.

In this video, you'll learn the basics on how to build and connect intelligent bots to interact with your users naturally wherever they are, from text/sms to Skype, Slack, Office 365 mail and other popular services. I explore the new Microsoft Bot Framework recently announced at Build 2016, which provides just what you need to build and connect intelligent bots that interact naturally wherever your users are talking.

Through simple demos I cover the Bot Builder SDK with C# (Node.js is also supported), the Bot Framework Emulator and I also explore how to handle natural language input from the user with the Language Understanding Intelligent Service (LUIS) from Microsoft Cognitive Services. Every business needs bots to provide a more personal experience to its users and customers. This video gives you the basics to get started in just 30 minutes, and then points you in the right direction to learn much more.

]]>https://channel9.msdn.com/Blogs/raw-tech/Build-Reaction-Cortana-and-the-Bot-FrameworkBots (or conversation agents) are rapidly becoming an integral part of your users' digital experience – they are as vital a way for users to interact with a service or application as is a web site or a mobile experience. Bots can also integrate with digital assistants like Cortana. Developers writing bots all face the same problems: bots require basic I/O; they must have language and dialog skills; and they must connect to users – preferably in any conversation experience and language the user chooses. In this video, you'll learn the basics on how to build and connect intelligent bots to interact with your users naturally wherever they are, from text/sms to Skype, Slack, Office 365 mail and other popular services. I explore the new Microsoft Bot Framework recently announced at Build 2016, which provides just what you need to build and connect intelligent bots that interact naturally wherever your users are talking. Through simple demos I cover the Bot Builder SDK with C# (Node.js is also supported), the Bot Framework Emulator and I also explore how to handle natural language input from the user with the Language Understanding Intelligent Service (LUIS) from Microsoft Cognitive Services. Every business needs bots to provide a more personal experience to its users and customers. This video gives you the basics to get started in just 30 minutes, and then points you in the right direction to learn much more. [00:00] Start - Teaser[00:17] Introduction - Why build bots?[04:38] Conversations as a Platform[06:12] Microsoft Bot Framework[09:15] Demo - Getting started with the Bot Framework[22:20] Demo - Alarm Bot, Natural Language Processing &amp; LUIS[28:53] Next steps, additional references &amp; more videosFeel free to ask me questions in the comments section below, or you can also contact me on Twitter at @ActiveNick. Follow @ActiveNick 1889https://channel9.msdn.com/Blogs/raw-tech/Build-Reaction-Cortana-and-the-Bot-Framework
Tue, 26 Apr 2016 12:30:00 GMThttps://channel9.msdn.com/Blogs/raw-tech/Build-Reaction-Cortana-and-the-Bot-FrameworkNick LandryNick Landry1https://channel9.msdn.com/Blogs/raw-tech/Build-Reaction-Cortana-and-the-Bot-Framework/RSSAzureNatural Language ProcessingCortanaExpert to Expert: Natural Language and Computational LinguisticsWikipedia: Computational linguistics is an
interdisciplinary field dealing with the
statistical and/or rule-based modeling of
natural language from a computational perspective. This modeling is not limited to any particular field of
linguistics. Traditionally, computational linguistics was usually performed by
computer scientists who had specialized in the application of computers to the processing of a
natural language. Computational linguists often work as members of interdisciplinary teams, including linguists (specifically trained in linguistics), language
experts (persons with some level of ability in the languages relevant to a given project), and computer scientists. In general computational linguistics draws upon the involvement of linguists,
computer scientists, experts in
artificial intelligence,
cognitive psychologists,
mathematicians, and
logicians, amongst others.

Here, we meet some of the scientists in Microsoft Research who work on computational linguistics. The great Erik Meijer conducts the interview. Special guests are: Researchers Chris
Quirk, Michael Gamon and Lucy Vanderwende. This is a great Expert to Expert since the Experts in this case are from different domains of expertise (Erik is a programming language specialist. The scientists Erik converses with are specialists in natural language
computation, linguisitics and mathematics). This is a fascinating conversation that spans topics from natural language processing to computing understanding (Yes. AI comes up...).

Enjoy! ]]>https://channel9.msdn.com/Blogs/Charles/Expert-to-Expert-Natural-Language-and-Computational-LinguisticsEver wonder what it takes to compute language (language in this case refers to what we humans speak and or/write)? From
Wikipedia: Computational linguistics is an
interdisciplinary field dealing with the
statistical and/or rule-based modeling of
natural language from a computational perspective. This modeling is not limited to any particular field of
linguistics. Traditionally, computational linguistics was usually performed by
computer scientists who had specialized in the application of computers to the processing of a
natural language. Computational linguists often work as members of interdisciplinary teams, including linguists (specifically trained in linguistics), language
experts (persons with some level of ability in the languages relevant to a given project), and computer scientists. In general computational linguistics draws upon the involvement of linguists,
computer scientists, experts in
artificial intelligence,
cognitive psychologists,
mathematicians, and
logicians, amongst others.Here, we meet some of the scientists in Microsoft Research who work on computational linguistics. The great Erik Meijer conducts the interview. Special guests are: Researchers Chris
Quirk, Michael Gamon and Lucy Vanderwende. This is a great Expert to Expert since the Experts in this case are from different domains of expertise (Erik is a programming language specialist. The scientists Erik converses with are specialists in natural language
computation, linguisitics and mathematics). This is a fascinating conversation that spans topics from natural language processing to computing understanding (Yes. AI comes up...).Enjoy! 3453https://channel9.msdn.com/Blogs/Charles/Expert-to-Expert-Natural-Language-and-Computational-Linguistics
Wed, 22 Oct 2008 18:34:00 GMThttps://channel9.msdn.com/Blogs/Charles/Expert-to-Expert-Natural-Language-and-Computational-LinguisticsCharlesCharles6https://channel9.msdn.com/Blogs/Charles/Expert-to-Expert-Natural-Language-and-Computational-Linguistics/RSSComputational LinguisticsErik MeijerExpert to ExpertMicrosoft ResearchMS ResearchNatural Language Processing